TURC - A DIAGNOSTIC MODEL OF CONTINENTAL GROSS PRIMARY PRODUCTIVITY AND NET PRIMARY PRODUCTIVITY

TURC, a diagnostic model for the estimation of continental gross prima ry productivity (GPP) and net primary productivity (NPP), is presented . This model uses a remotely sensed vegetation index to estimate the f raction of solar radiation absorbed by canopies, and an original param eterization of the relationship between absorbed solar radiation and G PP, based on measurements of CO2 fluxes above plant canopies. An indep endent, uncalibrated model of autotrophic maintenance and growth respi ration is parameterized from literature data, and uses databases on te mperature, biomass, and remotely sensed vegetation index. This model r esults in global estimates of GPP and NPP of 133.1 and 62.3 Gt(C) per year, respectively, which is consistent with commonly admitted values. The ratio of autotrophic respiration to GPP is about 70% for equatori al rain forests and 50% for temperate forests, as a result the highest predicted NPP are in tropical savannas of Africa and South America, a nd in temperate, highly cultivated zones of North America, not in equa torial rain forest zones. Conversion efficiencies defined as the ratio of yearly integrated NPP to absorbed photosynthetically active radiat ion (PAR) compare relatively well with a previous compilation of liter ature values, except for ecosystems with probable reduction of convers ion efficiency due to water stress. Several sensitivity studies are pe rformed on some input data sets, model assumptions, and model paramete rs.